An independent-measures study uses n = 15 participants in each group to compare two treatment conditions. What is the df value for the t statistic for this study?
One sample has M = 18 and a second sample has M = 14. If the pooled variance for the two samples is 16, what is the value of Cohen’s d?
Which combination of factors is most likely to produce a significant value for an independent-measures t statistic?
The data from an independent-measures research study produce a sample mean difference of 4 points and a pooled variance of 18. If there are n = 4 scores in each sample, what is the estimated standard error for the sample mean difference?
One sample has n = 10 scores and a variance of s2 = 20, and a second sample has n = 15
An independent-measures research study uses two samples, each with n = 10 participants. If the data produce a t statistic of t = 2.095, which of the following is the correct decision for a two-tailed hypothesis test?
Assuming a 5-point difference between the two sample means, which set of sample characteristics is most likely to produce a significant value for the independent- measures t statistic?
What is assumed by the homogeneity of variance assumption?
For the independent-measures t statistic, what is the effect of increasing the difference between sample means?
For an independent-measures t statistic, the estimated standard error measures how much difference is reasonable to expect between the sample means for two samples selected from the same population.
If an independent-measures t statistic has df = 20, then a total of 18 individuals participated in the research study.
For an independent-measures t statistic, you typically must compute the pooled variance before calculating the estimated standard error.
An independent-measures study has M1 = 49 and M2 = 45 with an estimated standard error of 4. For this study, Cohen’s d = 4/4 = 1.00.
If both samples have the same number of scores (n), then the independent-measures t statistic will have df = 2n – 2.
For a hypothesis test with the independent-measures t statistic, the null hypothesis states that the two population means are the same and the homogeneity assumption states that the two population variances are the same.